Don’t Let ‘Data’ Be an Afterthought in Your Data-Driven Initiatives

Don’t Forget the ‘Data’ When You Go ‘Data Driven’

If you are one of the lucky ones whose group or department was granted a budget to help your company take a more data driven marketing approach, congratulations! You have taken an important step on your way toward implementation. Get that kickoff going!

That’s good news. According to McKinsey Global Institute, data-driven organizations are 23 times more likely to acquire customers, six times more likely to retain customers, and 19 times more likely to be profitable. Obviously, leveraging data enables the enterprise to improve customer experience and make more informed decisions, keeping customers coming back for more!

But here’s a sobering truth. Back in 2015, Gartner estimated that 60% of big data projects fail. Later, Gartner analyst Nick Heudecker tweeted that Gartner had been “too conservative” with its estimate. The real failure rate, he said, was closer to 85%. (Since then, Heudecker’s tweet has been deleted.)

However, that shouldn’t stop you from being optimistic and visualizing the finish line. There’s a wealth of information out there provided by experts who themselves have gone through both successful and yet-to-be-successful implementations. Keep your focus on what’s important. That’s the topic we are going to discuss.

Tech: Don’t Be Distracted by the Bells and Whistles

When pursuing data-driven initiatives, much of the focus tends to fall on the shiniest part of the project: the technology. You know what I’m talking about – the platform, decision engine, database, appliance, automation software, etc. It’s not difficult to understand why, as tech consumes the majority of the discussion. Tech, most likely, is also the largest financial investment for the initiative. The majority of the budget and the proposal typically surrounds technology and integration. Rightfully so, as the tech will be active day to day for many years to come.

Having been part of several of these projects, I’m not going to contest the vast importance of technology in today’s data-driven initiatives. But here’s the thing: Though tech’s role is significant, it is NOT the most important factor. Falling into the trap that tech alone can fix your problems could put you in the 85% of the Gartner statistic.

I’ve attended several seminars and summits geared toward Chief Data Officers and found a striking commonality: There is a strong focus on technology but little attention given to the data itself. Even if the breakout sessions were about the data, the discussions would eventually find their way to technology. This echoes the Gartner sentiment, I feel.

Here are a few things that arguably carry the same weight, if not more, as technology in initiatives for a data-driven enterprise. You might be surprised by one or two of them.

1) Project Management

Yes, the unsung heroes of engagements: the “who” of all data initiatives. Enterprise data initiatives take time. In their due course (or in other scenarios, extended course), priorities, resources, and goals may prove to be moving targets. One would argue that making sure that there is a project management team overseeing the initiative is common sense, but at times common sense is not common practice. We’ve seen this role be overlooked due to many subject matter experts being present, however a team of subject matter experts is not the same as a team of project managers. Project managers do not just keep the schedule; they are the acting ombudsmen in the operation. They provide direction, the North Star when it’s needed the most.

2) Data Architecture and Policies

This is the “how,” “why,” and “when” of a data initiative. A properly articulated data architecture presents a clear understanding of the data and its transformation, management, and tracking. It also brings out into the open the source systems (integrated or siloed) and the process through which data is brought together. It will present the strengths and gaps to guide data management efforts in the future. Policies are just as important. They guide adherence to external and internal compliance requirements. Understanding the policies and your initiative’s adherence to (or disregard of) them can help improve your requirements and future-proof your data architecture and your data initiative as a whole.

3) The Data

We saved the best for last, but that’s literary liberty. Data comes first. Always. Data is the “what” in this scenario. It is the blood in your veins, the neurons in your nervous system, and the air in your respiratory system. Without data, there is no need for these structures. Data is the main ingredient in data-driven initiatives, yet as silly as it sounds, sometimes, the data itself is an afterthought in the system design. A CEO of a SaaS company once mentioned that moving to a data cloud solution from an exclusive on-premises instance will not solve any issue. It’s just garbage in a different location if you do not examine and make better the data you have before the migration. He’s correct. Technology can make things faster, absolutely. However, it can also make the transfer of garbage exponentially faster, making our problems even worse. Catalog, clean, inventory, interrogate, mend, and mind the data included in the initiative. Treat it not as an afterthought but as the reason why the initiative was needed to begin with. Make data your No. 1 focus in any data initiative.

Everything Works Together

Data is the most important aspect of a data-driven initiative, but it’s critically important to plan using policies and data architecture and to measure/guide execution through comprehensive project management. It’s so easy to throw in technology products as solutions to these projects, as some of them are quite well developed and instinctive to implement. No matter the situation, there will always be data use cases that are unique to your organization that would need additional effort for the technology to run in place. Your data will always reveal this. Get to know the data (what), then the data architecture (how), then the policies/procedures (why and how). Program management (who) guides the execution of the initiative. As for the tech? It applies only after you’ve accomplished the above.